Assessment of CD8 T cell immune activation markers to monitor response to antiretroviral therapy among HIV-1 infected patients in Côte d'Ivoire

Abstract

Because of the paucity of plasma HIV RNA viral load (VL) tests in resource-poor settings, the CD4(+) T cell count is often used as the sole laboratory marker to evaluate the effectiveness of antiretroviral therapy (ART) in HIV-infected patients. In untreated patients, the level of activated T cells is positively correlated with VL and represents a prognostic marker of HIV infection. However, little is known about its value to predict early drug failure, taking into account the relatively high non-specific immune activation background observed in many resource-limited tropical countries. We assessed the use of immune activation markers (expression of CD38 and/or human leucocyte antigen-DR on CD8(+) lymphocytes) to predict virological response to ART in a cohort of HIV-1 infected patients in Abidjan, Côte d'Ivoire. Correlations between VL, absolute CD4(+) T cell counts and immune activation levels were examined in 111 HIV patient samples at baseline and after 6 and 12 months of therapy. The percentage of CD38(+) CD8(+) T cells appeared to be the best correlate of VL. In contrast, changes in CD4(+) T cell counts provided a poor correlate of virological response to ART. Unfortunately, CD38(+) CD8(+) percentages lacked specificity for the determination of early virological drug failure and did not appear to be reliable surrogates of RNA viral load. CD38(+) CD8(+) T cell percentages may, rather, provide a sensitive estimate of the overall immune recovery, and be a useful extra laboratory parameter to CD4 counts that would contribute to improve the clinical management of HIV-infected people when VL testing facilities are lacking.

Fig. 1

Effect of treatment on virological and immunological markers of HIV-1 infection in the entire group (n = 111). The analyses were performed on data generated from a cohort of 111 HIV-infected patients. Results are presented as log₁₀ of RNA copy number (VL), absolute CD4⁺ T cell count or percentages of CD38⁺ cells within the CD8⁺ lymphocyte subsets. The box-plots represent the median, interquartile range (boxes) and the 5–95% data range (whisker caps). Asterisks and open circles represent extreme and outlier values, respectively. Comparison of each marker between different time-points have been made by the Wilcoxon signed-ranks tests for paired data. The level of significance was set at P < 0·05.

Fig. 2

Correlation between HIV-1 viral load and immunological parameters. Correlation between absolute CD4⁺ T cell count (a) and percentages of CD8⁺ T cells expressing CD38 (b) and/or HLA-DR (c, d) and RNA viral load calculated at baseline, months 6 and 12 by the Spearman rank correlation test (n = 111). The solid line represents the linear correlation between the two datasets. The equation was calculated after the outlier points (i.e. corresponding to the value of the cut off-point of the viral load assay) were excluded from the analysis.

Fig. 3

Receiver operating characteristic (ROC) curve of CD38⁺ CD8⁺ T cell percentages at month 6 in the extreme group (n = 36). The relationship between sensitivity (sens) and specificity (spec) of each immunological parameter to predict good or poor treatment response was studied in the extreme group (n = 36). Receiver operating characteristic curves were constructed by plotting the rate of true positive (sensitivity) against the rate of false positive (1-specificity) for all possible cut-off values at months 6 and 12. Only the ROC curve of CD38⁺ CD8⁺ T cell percentages at month 6 is presented. Cut-off values are displayed along the curve. The smallest cut-off values in the ROC curve is the minimum observed value minus 1 and the largest cut-off value is the maximum observed test value plus 1. All the other cut-off values are the average of two consecutive ordered observed values. The area under the ROC curve (AUC) is 0·877. The optimal operating point (90·91%), i.e. the cut-off giving the highest test accuracy, is associated with a relatively high rate of false negative (sens = 68·4%). This point lies on a 45° line closest to the north-west corner (0·1) of the ROC plot. For a more efficient screening of poor treatment response, a maximal sensitivity may be preferred by using 81·18% as the cut-off of positivity (sens = 100%; spec = 56·0%).